Let's have a chat!
PRAGUE, the Czech Republic – Unplanned downtime represents one of the major issues for manufacturers, causing loss of productivity and revenue, delays, and dissatisfaction among customers. According to Aberdeen Research, over 80% of producers recorded an unexpected downtime in the past three years, leading to an hourly cost of up to $260.000. A study by Vanson Bourne sponsored by ServiceMax revealed that more than 70% of manufacturers aren’t fully aware when their machines are due for maintenance, upgrade, or replacement. Other recent studies reported that downtime costs the industrial sector about $50 billion annually.
While manufacturers acknowledge the significance of downtime, they lack digitized tools and processes, data, time, and effective analysis methods, creating a need for developing and utilizing IIoT (Industrial Internet of Things) solutions.
With the increasing demand for automation and quality inspection across the industrial manufacturing sector, VISENSE enters a market with high potential. According to Grand View Research, the global machine vision market is projected to grow at a 7.7% CAGR from $14.3 billion in 2021 to $25.9 billion in 2030.
The AI technology VISENSE, developed by a Swiss team, brings industrial producers a solution to the ongoing downtime issue. Using industrial cameras and selected sensors, VISENSE provides manufacturers with insights to quickly identify and resolve unexpected visually-observable industrial machine errors. The software utilizes computer vision and machine learning to deliver error analysis and digitalize processes around the machines.
“VISENSE is able to autonomously detect and save all occurring machine error incidents and replace expensive process observation by machine operators and planners. The technology doesn’t need any data integration, is installed within minutes, and has versatile areas of application – whether shortening the ramp-up of new or optimizing machines in operation and makes processes that are undetectable to the bare eye visible.”
Christian Reich, the CEO and Co-Founder of VISENSE
The Swiss startup closed its pre-seed round of CHF 750.000 to develop further the AI and ML VISENSE software, backed by, besides AI Startup Incubator, Swiss Serpentine Ventures and Venture Kick, German HPI Seed Fund, and several Business Angels.
“Manufacturers will be able to purchase products that provide necessary AI capabilities without outside support, saving them the cost of hiring external resources to oversee their AI-related projects. This is one of the fundamental presumptions VISENSE is working on with its product development. It has created the “eyes” and “brain” of a system that watches over and controls industrial robots and machinery in specific production environments. VISENSE is the first in line for this enormous leap in a future where machines would monitor their own and other machines’ work to ensure quality,” says Angelo Burgarello, Business Director, Partner, and Investor at AI Startup Incubator.
With VISENSE, manufacturers are able to cut the time needed to identify, report, and resolve errors by up to 50%. Unlike other IIoT computer vision solutions, VISENSE exclusively focuses on machine processes to identify errors. And while the system requires machines to have automated and visually-observable processes, it can be applied to any industry.
“As a particle physicist, data scientist with IIoT experience, and business angel, I am extraordinarily impressed by the team. After discovering their deep knowledge of solving customer problems and their intellectual capability to generalize solutions of individual projects into a single scalable data-driven framework, I knew that I had to invest as much as I could,” says Dr. Dehua Zhu, Business Angel and Investor of VISENSE.
VISENSE has already attracted substantial potential clients in the automotive, packaging, and piping system sectors, including the BMW Group, with whom the startup successfully completed a PoC (Proof of Concept) project and is currently working on integrating the solution across their plants.
